September  2021, 11(3): 443-448. doi: 10.3934/naco.2020036

Application of survival theory in Mining industry

1. 

Institute of Mathematics and Digital Technology, Mongolian Academy of Sciences, National University of Mongolia

2. 

National University of Mongolia

3. 

Erdenet Mining Corporation, Erdenet, Mongolia

*Corresponding author: Enkhbat Rentsen

Received  April 2020 Revised  June 2020 Published  August 2020

Fund Project: This work was supported by the project of Business School of National University of Mongolia

The paper deals with an application of survival theory in mineral processing industry. We consider the problem of maximizing copper recovery and determine the best operating conditions based on survival theory. The survival of the system reduces to a problem of maximizing a radius of a sphere inscribed into a polyhedral set defined by the linear regression equations for a flotation process. To demonstrate the effectiveness of the proposed approach, we present a case study for the rougher flotation process of copper-molybdenum ores performed at the Erdenet Mining Corporation(Mongolia).

Citation: Enkhbat Rentsen, N. Tungalag, J. Enkhbayar, O. Battogtokh, L. Enkhtuvshin. Application of survival theory in Mining industry. Numerical Algebra, Control & Optimization, 2021, 11 (3) : 443-448. doi: 10.3934/naco.2020036
References:
[1]

L. T. Ashepkov and U. Badam, Models and Methods of Survival Theory for Controlled System, Vladivostok: DalNauka, 2006. Google Scholar

[2]

U. Badam, A simple model of improving survival in economical systems, Optimization of Control (Eds. P. M. Pardalos, I. Tseveendorj and R. Enkhbat), World Scientific, (2003), 287–295. Google Scholar

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U. Badam, Optimality conditions for problems of survival theory, Izvestiya Vuzov, 2 (2002), 18-22.   Google Scholar

[4]

U. Badam, Models and problems of survival theory for linear discrete system, Intellect and Control, (2002), 35–50. Google Scholar

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U. Badam, R. Enkhbat and Ts. Batchimeg, Application of survival theory in taxation, Journal of Indusdrial and Management Optimization, accepted and to appear in 2020. Google Scholar

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S. S. Cham. RathH. Sahoo and B. Das, Optimization of flotation variables for the recovery of hematite particles from BHQ Ore, Int. J. Miner. Metall. Mater., 20 (2013), 605-611.   Google Scholar

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R. EnkhbatT. V. Gruzdeva and M. V. Barkova, D. C. programming approach for solving an applied ore-processing problem, Journal of Indusdrial and Management Optimization, 14 (2018), 613-623.  doi: 10.3934/jimo.2017063.  Google Scholar

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Thomas R. Fleming and David P. Harrington, Counting Processes and Survival Analysis, Wiley, 1991.  Google Scholar

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T. V. GruzdevaA. V. Ushakov and R. Enkhbat, A bioobjective d.c programming approach to optimization of rougher flotation process, Computers and Chemical Engineering, 108 (2018), 349-359.   Google Scholar

[13]

C. Huber, N. Limnios, M. Meshbah and M. Nikulin, Mathematical Methods in Survival Analysis, Reliability and Quality of Life, Wiley, 2008. doi: 10.1002/9780470610985.  Google Scholar

[14]

X. Liu, Survival Analysis(Models and Applications), Wiley, 2012. Google Scholar

[15]

M. MaldonadoD. Sbarbaro and E. Lizama, Optimal control of a rougher flotation process based on dynamic programming, Miner. Eng., 20 (2007), 221-232.   Google Scholar

[16]

D. A. MendezE. D. Gálvez and L. A. Cisternas, State of the art in the conceptual design of flotation circuits, Int. J. Miner. Process., 90 (2009), 1-15.   Google Scholar

[17]

D. PirouzanM. Yahyaei and S. Banisi, Pareto based optimization of flotation cells configuration using an oriented genetic algorithm, Int. J. Miner. Process., 126 (2014), 107-116.   Google Scholar

[18]

B. J. Shean and J. J. Cilliers, A review of froth flotation control, Int. J. Miner. Process., 100 (2011), 57-71.   Google Scholar

[19]

A. S. Strekalovsky, Global optimality conditions and exact penalization, Optimization Letters, 13 (2019), 597-615.  doi: 10.1007/s11590-017-1214-x.  Google Scholar

[20]

G. Zimmermann, From Basic Survival Analytic Theory to a Non-Standard Application, Springer, 2017.  Google Scholar

show all references

References:
[1]

L. T. Ashepkov and U. Badam, Models and Methods of Survival Theory for Controlled System, Vladivostok: DalNauka, 2006. Google Scholar

[2]

U. Badam, A simple model of improving survival in economical systems, Optimization of Control (Eds. P. M. Pardalos, I. Tseveendorj and R. Enkhbat), World Scientific, (2003), 287–295. Google Scholar

[3]

U. Badam, Optimality conditions for problems of survival theory, Izvestiya Vuzov, 2 (2002), 18-22.   Google Scholar

[4]

U. Badam, Models and problems of survival theory for linear discrete system, Intellect and Control, (2002), 35–50. Google Scholar

[5]

U. Badam, R. Enkhbat and Ts. Batchimeg, Application of survival theory in taxation, Journal of Indusdrial and Management Optimization, accepted and to appear in 2020. Google Scholar

[6]

D. Carl FreemanLionel G. Klikoff and He nry Eyringt, Applications of the survival theory to ecology, Proc. Nat. Acad. Sci. USA, 11 (1974), 4332-4335.   Google Scholar

[7]

S. S. Cham. RathH. Sahoo and B. Das, Optimization of flotation variables for the recovery of hematite particles from BHQ Ore, Int. J. Miner. Metall. Mater., 20 (2013), 605-611.   Google Scholar

[8]

R. Enkhbat, Global optimization approach to Malfatti's problem, Journal of Global Optimization, 65 (2016), 3-39.  doi: 10.1007/s10898-015-0372-6.  Google Scholar

[9]

R. Enkhbat, Convex maximization formulation of general sphere packing problem, Izv. Irkutsk. Gos. Univ. Ser. Mat., 31 (2020), 142-149.   Google Scholar

[10]

R. EnkhbatT. V. Gruzdeva and M. V. Barkova, D. C. programming approach for solving an applied ore-processing problem, Journal of Indusdrial and Management Optimization, 14 (2018), 613-623.  doi: 10.3934/jimo.2017063.  Google Scholar

[11]

Thomas R. Fleming and David P. Harrington, Counting Processes and Survival Analysis, Wiley, 1991.  Google Scholar

[12]

T. V. GruzdevaA. V. Ushakov and R. Enkhbat, A bioobjective d.c programming approach to optimization of rougher flotation process, Computers and Chemical Engineering, 108 (2018), 349-359.   Google Scholar

[13]

C. Huber, N. Limnios, M. Meshbah and M. Nikulin, Mathematical Methods in Survival Analysis, Reliability and Quality of Life, Wiley, 2008. doi: 10.1002/9780470610985.  Google Scholar

[14]

X. Liu, Survival Analysis(Models and Applications), Wiley, 2012. Google Scholar

[15]

M. MaldonadoD. Sbarbaro and E. Lizama, Optimal control of a rougher flotation process based on dynamic programming, Miner. Eng., 20 (2007), 221-232.   Google Scholar

[16]

D. A. MendezE. D. Gálvez and L. A. Cisternas, State of the art in the conceptual design of flotation circuits, Int. J. Miner. Process., 90 (2009), 1-15.   Google Scholar

[17]

D. PirouzanM. Yahyaei and S. Banisi, Pareto based optimization of flotation cells configuration using an oriented genetic algorithm, Int. J. Miner. Process., 126 (2014), 107-116.   Google Scholar

[18]

B. J. Shean and J. J. Cilliers, A review of froth flotation control, Int. J. Miner. Process., 100 (2011), 57-71.   Google Scholar

[19]

A. S. Strekalovsky, Global optimality conditions and exact penalization, Optimization Letters, 13 (2019), 597-615.  doi: 10.1007/s11590-017-1214-x.  Google Scholar

[20]

G. Zimmermann, From Basic Survival Analytic Theory to a Non-Standard Application, Springer, 2017.  Google Scholar

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